| bicorAndPvalue | R Documentation | 
A faster, one-step calculation of Student correlation p-values for multiple biweight midcorrelations, properly taking into account the actual number of observations.
bicorAndPvalue(x, y = NULL, 
             use = "pairwise.complete.obs", 
             alternative = c("two.sided", "less", "greater"),
             ...)
| x | a vector or a matrix | 
| y | a vector or a matrix. If  | 
| use | determines handling of missing data. See  | 
| alternative | specifies the alternative hypothesis and must be (a unique abbreviation of) one of
 | 
| ... | other arguments to the function  | 
The function calculates the biweight midcorrelations of a matrix or of two matrices 
and the corresponding Student p-values.
The output is not as full-featured as cor.test, but can work with matrices as input.
A list with the following components, each a marix:
| bicor | the calculated correlations | 
| p | the Student p-values corresponding to the calculated correlations | 
| Z | Fisher transform of the calculated correlations | 
| t | Student t statistics of the calculated correlations | 
| nObs | Numbers of observations for the correlation, p-values etc. | 
Peter Langfelder and Steve Horvath
Peter Langfelder, Steve Horvath (2012) Fast R Functions for Robust Correlations and Hierarchical Clustering. Journal of Statistical Software, 46(11), 1-17. https://www.jstatsoft.org/v46/i11/
bicor for calculation of correlations only;
cor.test for another function for significance test of correlations
# generate random data with non-zero correlation
set.seed(1);
a = rnorm(100);
b = rnorm(100) + a;
x = cbind(a, b);
# Call the function and display all results
bicorAndPvalue(x)
# Set some components to NA
x[c(1:4), 1] = NA
corAndPvalue(x)
# Note that changed number of observations.
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